Abstract

PV strings are essential for energy conversion in large-scale photovoltaic (PV) power plants. The operating state of PV strings directly affects the power generation efficiency and economic benefits of PV power plants. In the process of evaluating PV arrays, a reference array needs to be identified. By comparing PV arrays with the reference array, the operational status of the PV arrays can be evaluated. However, in the actual operation of PV power stations, it is difficult to directly determine the reference state of a PV array due to random fluctuations in the PV power output. In order to solve the problems mentioned above, this paper proposes a method to select the reference state and perform a grading evaluation of PV strings. Additionally, the proposed method is based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm, which is used to rank the performance of PV arrays to determine their status. In order to solve the problem of random fluctuations in PV power generation, a probability distribution model of the PV string conversion efficiency was built by using the kernel density estimation method. Then, the characteristic indicator of the PV string’s operating state was described by the output power of the PV string and its probability distribution model. Then, based on the operating characteristic indicator, the reference state of the PV string was determined using the TOPSIS method, and the grading evaluation of the operating state of the PV string was realized. Finally, the effectiveness of the proposed method was verified using the actual data of a PV power station.

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